Clinical Data Manager

Position Summary

The Clinical Data Manager will oversee clinical cohort data from start to finish, with a focus on quality control, analysis, and reliable data delivery. This person will safeguard data accuracy, spot and correct inconsistencies, and work closely with laboratory operations and bioinformatics engineering teams. The role also supports clinical data pipelines, investigates unusual findings, and contributes to MRD-oriented analysis, process refinements, and research work.

Clinical Data Management & Quality Control

• Maintain and monitor clinical cohorts while preserving accurate sample metadata and end-to-end traceability.
• Carry out QC checks, validation reviews, and documentation of deviations across datasets.
• Detect, review, and resolve data anomalies such as contamination, sample mix-ups, or results that do not match expectations.
• Keep clinical datasets reproducible, traceable, and ready for audit review.

Data Investigation & Pipeline Interaction

• Use statistical and bioinformatics methods to investigate data irregularities.
• Operate and monitor pipelines used for reprocessing and data correction.
• Work with bioinformatics pipelines through command-line tools and scripting.
• Diagnose issues across the full flow, from raw inputs to final outputs.

Cross-Functional Collaboration

• Serve as the communication bridge between Lab Operations and Bioinformatics Engineering.
• Help speed up issue resolution so data can be delivered on time.
• Present conclusions clearly and escalate concerns when needed.

Data Systems & Reporting

• Use internal databases and fix data mismatches or inconsistencies.
• Create dashboards to track cohort status, QC measures, and delivery schedules.
• Prepare reports that summarize data quality, deviations, and investigation outcomes.

Advanced Analysis & Research Support

• Analyze unblinded clinical datasets in depth.
• Detect biological signals, technical artifacts, and sources of noise, especially in MRD-related work.
• Use data findings to improve pipelines and QC rules.
• Support new assay development and analytical methods.
• Contribute to publications, internal documentation, and regulatory materials.

Regulatory & External Collaboration

• Assist with documentation needed for regulatory submissions and audit preparation.
• Prepare clinical datasets for external collaborators.
• Coordinate data transfer, submission, and tracking across multiple studies.

Requirements

• PhD in Bioinformatics, Computational Biology, Statistics, or a related discipline.
• At least 3 to 7+ years of experience in clinical data management or clinical genomics.
• Strong hands-on experience with NGS data, including MRD analysis.
• Proficiency in Python, including pandas or similar libraries for data analysis.
• Experience working with SQL or other database systems.
• Comfort using Linux/Unix systems and command-line utilities.
• Strong statistical reasoning and analytical problem-solving ability.
• Ability to collaborate across functions in a fast-moving environment.

Preferred Experience

• Background in tumor-normal and cfDNA workflows.
• Experience creating dashboards or tracking tools.
• Understanding of GCP and regulatory workflows.
• Prior involvement in submissions and publication support.